Louis Miguel Bernal, AI Data Engineer and Full-Stack Software Engineer: Built to scale, run in production.Built to scale,run in production.スケールを前提に、本番で動かす。为规模而生，在生产环境中运行。Создано расти,работает в проде.स्केल के लिए बना,प्रोडक्शन में चलता।

Responsibilities

• Built AWS Bedrock LLM services over the warehouse: document intelligence parsing loan files, appraisals and financials at 95% field accuracy, a confidence-scored entity-resolution matcher reconciling hundreds of properties against a 14K-row regulatory registry, and a RAG copilot on the Snowflake semantic layer, cutting manual entry 80%.
• Architected and own the Airflow DAG ingestion layer across 3 core source systems (Hypha, NetSuite and iLevel), merging into tiered Snowflake raw schemas with source and load-timestamp lineage columns and moving 500K+ records/day at 99.9% uptime behind keyset-paged loaders and loud-failure schema-drift guards.
• Engineered a multi-layer dbt transformation backbone on Snowflake (staging, intermediate, export and mart layers, 80+ models), standardizing 40+ tables behind reusable data-quality and performance-metric test macros and a severity-tagged validation catalogue, cutting model build and QC time 60%.
• Delivered the finance and accounting pipelines the business runs on, rebuilding a portfolio valuation model to a 99.7% identity match against the reporting tape, shipping general-ledger ingestion with automated reconciliation checks, and automating an underwriting-to-asset-system sync with read-compare-write logic that never overwrites a human entry.